Python theme_mm Exemples

Exemple #1

Fichier : histogram_1.py Projet : hydrosquall/mmviz-python

import numpy as np
import pandas as pd

import matplotlib
import matplotlib.pyplot as plt

import mmviz

matplotlib.style.use("mmviz")

mmviz.scale_palette_mm("qual_fill")

df = pd.read_csv("../data/diamonds.csv")

bin_width = 500
bins = mmviz.create_bin_list(df['price'], bin_width)

df = df.pivot(columns='cut', values="price")
ax = df.plot.hist(stacked=True, bins=bins)
ax.set_title("Distribtion of Diamond Price by Cut")
mmviz.theme_mm(ax, "histogram")

plt.xlabel("Price (bin width = 500)")

mmviz.place_legend(plt, "Cut", 0.2)

plt.savefig("./images/histogram_1", dpi=100)
plt.show()

Exemple #2

Fichier : series.py Projet : hydrosquall/mmviz-python

import numpy as np
import pandas as pd

import matplotlib
import matplotlib.pyplot as plt

import mmviz

matplotlib.style.use("mmviz")

mmviz.scale_palette_mm("qual_color")

df = pd.DataFrame(np.random.randn(1000, 4), index=pd.date_range('1/1/2000', periods=1000), columns=list('ABCD'))
df = df.cumsum()
ax = df.plot()
ax.set_title("Random Value Over Time")
mmviz.theme_mm(ax, "line")

plt.xlabel("Time")
plt.ylabel("Value")

mmviz.place_legend(plt, "Category", 0.15)

plt.savefig("./images/series", dpi=100)
plt.show()

Exemple #3

Fichier : box_1.py Projet : hydrosquall/mmviz-python

import numpy as np
import pandas as pd

import matplotlib
import matplotlib.pyplot as plt

import mmviz

matplotlib.style.use("mmviz")

df = pd.read_csv("../data/diamonds.csv")

ax = df[['cut', 'price']].boxplot(by="cut", column="price")
ax.set_title("Distribtion of Price by Cut")
mmviz.theme_mm(ax, "box")

plt.xlabel("Cut")
plt.ylabel("Price")

plt.savefig("./images/box_1", dpi=100)

plt.show()

Exemple #4

import numpy as np
import pandas as pd

import matplotlib
import matplotlib.pyplot as plt

import mmviz

matplotlib.style.use("mmviz")

df = pd.read_csv("../data/diamonds.csv")
df1 = df.groupby('clarity').size()
df1.sort_values(ascending=False, inplace=True)

ax = df1.plot.bar(rot=0)
ax.set_title("Diamonds by Clarity")
mmviz.theme_mm(ax, "bar")

plt.xlabel("Clarity")
plt.ylabel("Frequency")

plt.savefig("./images/bar", dpi=100)
plt.show()

Exemple #5

cols = ["cyl", "mpg", "wt", "disp"]

df_cyl_dict = {
    "Cyl 4": df.loc[df["cyl"] == 4, cols],
    "Cyl 6": df.loc[df["cyl"] == 6, cols],
    "Cyl 8": df.loc[df["cyl"] == 8, cols]
}

palette_iter = mmviz.get_palette_iter_mm("qual_fill")

ax = None
for key in df_cyl_dict:
    ax = df_cyl_dict[key].plot.scatter(x="wt",
                                       y="mpg",
                                       label=key,
                                       c=next(palette_iter),
                                       s=df_cyl_dict[key]["disp"],
                                       ax=ax,
                                       alpha=0.8)

ax.set_title("Weight vs. Miles Per Gallon")
mmviz.theme_mm(ax, "scatter")

plt.xlabel("Car Weight")
plt.ylabel("Miles Per Gallon")

mmviz.place_legend(plt, "Cylinder", 0.2)

plt.savefig("./images/scatter", dpi=100)
plt.show()

Exemple #6

import numpy as np
import pandas as pd

import matplotlib
import matplotlib.pyplot as plt

import mmviz

matplotlib.style.use("mmviz")

df = pd.read_csv("../data/diamonds.csv")
df1 = df.groupby('clarity').size()
df1.sort_values(ascending=True, inplace=True)

ax = df1.plot.barh(rot=0)
ax.set_title("Diamonds by Clarity")
mmviz.theme_mm(ax, "bar-horizontal")

plt.xlabel("Clarity")
plt.ylabel("Frequency")

plt.savefig("./images/bar", dpi=100)
plt.show()